My set of ongoing projects is rather dynamic, so that any
specific list will be nearly always outdated. However, it is
fair to say that much of my work revolves around the following
themes: game theory in security (with forays into both physical
and cyber security) and privacy (particularly health data
privacy), innovation diffusion and marketing (especially with a
machine learning/data mining twist), robust (especially
adversarial) machine learning, computational vaccine design, and computational game
theory and mechanism design.
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Most of my research work crosses disciplinary boundaries. My technical
background is in Artificial Intelligence, with a Ph.D. in Computer Science
and Engineering from the University of Michigan under supervision of Michael
P. Wellman. Much of my work is in Multiagent Systems, at the intersection
of Computer Science and Economics (especially Game Theory). I
particularly enjoy applied concepts from game theory to a
broad array of problems, such as optimal security
resource allocation, robust machine learning, risk
analysis of health data de-identification strategies, and game
theoretic design of broadly neutralizing antibodies.
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